Amazon Technologies, Inc.

James Connelly Petts

Jesper Mikael Johansson

Harsha Ramalingam

Aaron James Dykstra

Laura Ellen Grit

Dominique Imjya Brezinski

George M Ionkov

Samuel A Minter

Dennis H Harding

Lindsey Christina Fowler

Yong Xi

Jon Arron McClintock

Timothy Mark Edward Bollefer

Tom Killalea

Vivek A Shah

Olga I Kuznetsova

Roy N Harkness

Alexander S Borst

Michael R Brauwerman

Theodore H Romer

Dominique I Brezinkski

A user device displays portions of an electronic publication for a user to read. The user device tracks the user's reading behavior of the portions of the electronic publication. The user device then suggests additional reading material for the user based on the user's reading behavior.

Reading material suggestions based on reading behavior

Disclosed are various embodiments for active data that tracks usage. The active data includes instructions that are executable by a computing device. The computing device is scanned to identify characteristics of the computing device. The characteristics of the computing device are utilized to determine whether the usage of the active data is authorized. Data is transmitted to a network service, including identifying information for the particular computing device and data that identifies a deployment of the active data.

Identifying data usage via active data

A customized questionnaire is generated for a content item, such as an eBook, audio file, video file, and so on. Upon an occurrence of predetermined event, the user is presented with the customized questionnaire soliciting responses to questions and/or rating evaluations relating to the content item. The responses may include reviews, ratings, recommendations of similar items, discussion topics, and other things. Information from the responses may be collected and associated with the content item to build a user-driven index.

Categorization based on user questionnaire

Disclosed are various embodiments for obtaining policy data specifying decoy data eligible to be inserted within a response to an access of a data store. The decoy data is detected in the response among a plurality of non-decoy data based at least upon the policy data. An action associated with the decoy data is initiated in response to the access of the data store meeting a configurable threshold.

Adapting decoy data present in a network

Content is distributed electronically to a plurality of users. As the users consume the content, they may annotate the content to indicate corrections, comments, or other information. Annotations are collected at a server and reported back to content creators, such as authors, publishers, translators, editors, etc.

Annotations for content creation feedback

Disclosed are various embodiments for active data, such as active decoy data. The active decoy data includes instructions that, when executed by a particular device, cause the particular computing device to determine whether the particular computing device is a target computing device. The particular computing device initiates a predefined action in response to determining that the particular computing device is not the target computing device. The approaches described herein may also be useful in wrapping and distributing digital content.

Electronic content items such as electronic books are enhanced by identifying citations within the content items, identifying sources of the objects of the citations, and associating the citations with such sources so that readers of the content items can easily purchase or otherwise obtain the citation objects. The citations may be updated as new products become available or information related to the products changes over time.

eBook citation enhancement

Database Definition Language (DDL) transactions are defined that include one or more DDL operations that are to be executed to modify aspects of a relational database, such as its structure. If performance of one or more of the DDL operations in a DDL transaction fails, then the changes made to the relational database by some or all of the DDL operations may be reversed. Instructions and state information may be generated and stored prior to, during, and/or following the execution of a DDL operation that may be utilized to reverse the changes to a relational database made by the DDL operations. User interfaces might also be provided for defining, selecting, editing, and executing DDL transactions, and for providing information relating to the execution and rollback of DDL operations in a DDL transaction.

Transactional control of RDBMS database definition language operations

Disclosed are various embodiments for identifying a table of non-decoy data matching a set of criteria. Decoy data is inserted into the table of non-decoy data. The decoy data is detected in a result comprising the decoy data, the result generated in response to an access of the data store. An alarm is generated based at least upon the result.

Use of decoy data in a data store

A user device displays portions of an electronic publication for a user to read. The user device tracks the user's reading behavior of the portions of the electronic publication. The user device then selects a problem from a group of pre-generated problems for the user based on the user's reading behavior and provides the selected problem to the user.

User device providing electronic publications with dynamic exercises

User content access events pertaining to a content item, such as an eBook, audio, video file, and so on, are collected and analyzed to determine progress data, including completion information about when the content item, or a portion thereof, has been completed. Once determined, further information or recommendations that have some relation to the completed content item may be presented to the user.

Content completion recommendations

Disclosed are various embodiments for generating automobile parts bundles associated with maintenance events. A maintenance schedule is retrieved and various maintenance events are identified. Various maintenance tasks associated with maintenance events are also identified. Parts associated with these maintenance tasks are placed into parts bundles associated with the maintenance event and a unique identifier within a parts catalog.

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Redmond, WA, United States of America

James Connelly Petts